FAIR data management practices to introduce circular economy in aquaculture: benefits, barriers and a preliminary roadmap

FAIR (Findable, Accessible, Interoperable and Reusable) data principles stand out as critical to ensure that data can be efficiently shared and used across diverse scientific, academic, and industrial domains, facilitating interoperability and informed decision making. However, industrial players are often reluctant to embrace FAIR data principles due to reasons such as the fear of losing competitive advantage and the lack of resources to convert their datasets. This study is one of the few attempts to shed light on the advantages FAIR data can offer, highlighting adoption drivers and barriers with a focus on the aquaculture industry. The research is developed relying on a mixed methodology consisting of semi-structured qualitative interviews and quantitative questionnaires addressed to a selected group of relevant stakeholders. As a result of the study, six policy recommendations of political, technological, social and environmental nature are offered to outline a path towards a more sustainable and efficient aquaculture industry, supported by measurable KPIs to assess their impact. The results collected by this study stress the importance of available FAIR datasets across platforms. Perhaps more importantly, they allow the classification of the benefits of key circular economy (CE) and FAIR data management practices for the aquaculture sector, as well as current main adoption barriers and enablers. Key barriers include data acquisition costs, lack of skills and knowledge of FAIR data benefits, concerns and confusion with open data and lack of investments in interoperable solutions. In contrast, key enablers include cost reduction to acquire data, best-practice regulations, awareness of FAIR benefits, education to innovation, collaboration incentives and complexity reduction through standardised solutions. Although the timely implementation of this study’s final recommendation roadmap could favour impactful legislative changes to implement a more sustainable and efficient aquaculture sector, reliance on political will and targeted policymaking actions will in all likelihood delay their effective implementation.

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Publication Details

Journal
International Journal of Data Science and Analytics
Published
2025-04-13
DOI
https://doi.org/10.1007/s41060-025-00765-4
Citations
4
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
12.98

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article

FAIR data management practices to introduce circular economy in aquaculture: benefits, barriers and a preliminary roadmap

Rita Giuffrida, Ian D. Broadbent, Maria Grazia Giuffrida, Claudio de Majo
4 citations
International Journal of Data Science and Analytics
Research Data Management Practices
12.98
article

FAIR data management practices to introduce circular economy in aquaculture: benefits, barriers and a preliminary roadmap

Rita Giuffrida, Ian D. Broadbent, Maria Grazia Giuffrida, Claudio de Majo
article en
4 citations

Abstract

FAIR (Findable, Accessible, Interoperable and Reusable) data principles stand out as critical to ensure that data can be efficiently shared and used across diverse scientific, academic, and industrial domains, facilitating interoperability and informed decision making. However, industrial players are often reluctant to embrace FAIR data principles due to reasons such as the fear of losing competitive advantage and the lack of resources to convert their datasets. This study is one of the few attempts to shed light on the advantages FAIR data can offer, highlighting adoption drivers and barriers with a focus on the aquaculture industry. The research is developed relying on a mixed methodology consisting of semi-structured qualitative interviews and quantitative questionnaires addressed to a selected group of relevant stakeholders. As a result of the study, six policy recommendations of political, technological, social and environmental nature are offered to outline a path towards a more sustainable and efficient aquaculture industry, supported by measurable KPIs to assess their impact. The results collected by this study stress the importance of available FAIR datasets across platforms. Perhaps more importantly, they allow the classification of the benefits of key circular economy (CE) and FAIR data management practices for the aquaculture sector, as well as current main adoption barriers and enablers. Key barriers include data acquisition costs, lack of skills and knowledge of FAIR data benefits, concerns and confusion with open data and lack of investments in interoperable solutions. In contrast, key enablers include cost reduction to acquire data, best-practice regulations, awareness of FAIR benefits, education to innovation, collaboration incentives and complexity reduction through standardised solutions. Although the timely implementation of this study’s final recommendation roadmap could favour impactful legislative changes to implement a more sustainable and efficient aquaculture sector, reliance on political will and targeted policymaking actions will in all likelihood delay their effective implementation.

International Journal of Data Science and AnalyticsVol. 20(5)
Education Trust (US), Broadcom (United Kingdom) (GB)
European Commission
Openalex Percentile: Top 2%
Research Data Management Practices
12.98
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